Intelligent assisted living framework for monitoring elders

Recently, Ambient Intelligence Systems (AmI) in particular Ambient Assisted Living (AAL) are attracting intensive research due to a large variety of application scenarios and an urgent need for elderly in-home assistance. AAL is an emerging multi-disciplinary paradigm aiming at exploiting information and communication technologies in personal healthcare and telehealth systems for countering the effects of growing elderly population. AAL systems are developed to help elderly people living independently by monitoring their health status and providing caregivers with useful information. However, strong contributions are yet to be made on context binding of newly discovered sensors for providing dynamic or/and adaptive UI for caregivers, as the existing solutions (including framework, systems and platforms) are mainly focused on checking user operation history, browser history and applications that are most used by a user for prediction and display of the applications to an individual user. The aim of this paper is to propose a framework for making the adaptive UI from context information (real-time and historical data) that is collected from caregivers (primary user) and elderly people (secondary user). The collected data is processed to produce the contextual information in order to provide assistive services to each individual caregiver. To achieve this, the proposed framework collects the data and it uses a set of techniques (including system learning, decision making) and approaches (including ontology, user profiling) to integrate assistive services at runtime and enable their bindings to specific caregivers, in so doing improving the adaptability parameter of UI for the AAL. © 2017 IEEE

Designing a gamified social platform for people living with dementia and their live-in family caregivers

In the current paper, a social gamified platform for people living with dementia and their live-in family caregivers, integrating a broader diagnostic approach and interactive interventions is presented. The CAREGIVERSPRO-MMD (C-MMD) platform constitutes a support tool for the patient and the informal caregiver - also referred to as the dyad - that strengthens self-care, and builds community capacity and engagement at the point of care. The platform is implemented to improve social collaboration, adherence to treatment guidelines through gamification, recognition of progress indicators and measures to guide management of patients with dementia, and strategies and tools to improve treatment interventions and medication adherence. Moreover, particular attention was provided on guidelines, considerations and user requirements for the design of a User-Centered Design (UCD) platform. The design of the platform has been based on a deep understanding of users, tasks and contexts in order to improve platform usability, and provide adaptive and intuitive User Interfaces with high accessibility. In this paper, the architecture and services of the C-MMD platform are presented, and specifically the gamification aspects. © 2018 Association for Computing Machinery.Peer ReviewedPostprint (author's final draft

Authentication and authorisation in entrusted unions

This paper reports on the status of a project whose aim is to implement and demonstrate in a real-life environment an integrated eAuthentication and eAuthorisation framework to enable trusted collaborations and delivery of services across different organisational/governmental jurisdictions. This aim will be achieved by designing a framework with assurance of claims, trust indicators, policy enforcement mechanisms and processing under encryption to address the security and confidentiality requirements of large distributed infrastructures. The framework supports collaborative secure distributed storage, secure data processing and management in both the cloud and offline scenarios and is intended to be deployed and tested in two pilot studies in two different domains, viz, Bio-security incident management and Ambient Assisted Living (eHealth). Interim results in terms of security requirements, privacy preserving authentication, and authorisation are reported

An assisted navigation method for telepresence robots

Telepresence robots have emerged as a new means of interaction in remote environments. However, the use of such robots is still limited due to safety and usability issues when operating in human-like environments. This work addresses these issues by enhancing the robot navigation through a collaborative control method that assists the user to negotiate obstacles. The method has been implemented in a commercial telepresence robot and a user study has been conducted in order to test the suitability of our approach.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Design process enabling adaptation in pervasive heterogeneous contexts

International audienceIn the next decades, the growth in population ageing will cause important problems to most industrialized countries. To tackle this issue, Ambient Assistive Living (AAL) systems can reinforce the well-being of elderly people, by providing emergency, autonomy enhancement, and comfort services. These services will postpone the need of a medicalized environment, and will allow the elderly to stay longer at home. However, each elderly has specific needs and a deployment environment of such services is likely unique. Furthermore, the needs evolve over time, and so does the deployment environment of the system. In this paper, we propose the use of a model-based development method, the adaptive medium approach, to enable dynamic adaptation of AAL systems. We also propose improvements to make it more suited to the AAL domain, such as considering heterogeneity and a composition model. The paper includes an evaluation of the prototype implementing the approach, and a comparison with related work

Ambient Assisted Living: Scoping Review of Artificial Intelligence Models, Domains, Technology, and Concerns

Background: Ambient assisted living (AAL) is a common name for various artificial intelligence (AI)—infused applications and platforms that support their users in need in multiple activities, from health to daily living. These systems use different approaches to learn about their users and make automated decisions, known as AI models, for personalizing their services and increasing outcomes. Given the numerous systems developed and deployed for people with different needs, health conditions, and dispositions toward the technology, it is critical to obtain clear and comprehensive insights concerning AI models used, along with their domains, technology, and concerns, to identify promising directions for future work. Objective: This study aimed to provide a scoping review of the literature on AI models in AAL. In particular, we analyzed specific AI models used in AАL systems, the target domains of the models, the technology using the models, and the major concerns from the end-user perspective. Our goal was to consolidate research on this topic and inform end users, health care professionals and providers, researchers, and practitioners in developing, deploying, and evaluating future intelligent AAL systems. Methods: This study was conducted as a scoping review to identify, analyze, and extract the relevant literature. It used a natural language processing toolkit to retrieve the article corpus for an efficient and comprehensive automated literature search. Relevant articles were then extracted from the corpus and analyzed manually. This review included 5 digital libraries: IEEE, PubMed, Springer, Elsevier, and MDPI. Results: We included a total of 108 articles. The annual distribution of relevant articles showed a growing trend for all categories from January 2010 to July 2022. The AI models mainly used unsupervised and semisupervised approaches. The leading models are deep learning, natural language processing, instance-based learning, and clustering. Activity assistance and recognition were the most common target domains of the models. Ambient sensing, mobile technology, and robotic devices mainly implemented the models. Older adults were the primary beneficiaries, followed by patients and frail persons of various ages. Availability was a top beneficiary concern. Conclusions: This study presents the analytical evidence of AI models in AAL and their domains, technologies, beneficiaries, and concerns. Future research on intelligent AAL should involve health care professionals and caregivers as designers and users, comply with health-related regulations, improve transparency and privacy, integrate with health care technological infrastructure, explain their decisions to the users, and establish evaluation metrics and design guidelines. Trial Registration: PROSPERO (International Prospective Register of Systematic Reviews) CRD42022347590; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022347590This work was part of and supported by GoodBrother, COST Action 19121—Network on Privacy-Aware Audio- and Video-Based Applications for Active and Assisted Living

Evaluating XMPP Communication in IEC 61499-based Distributed Energy Applications

The IEC 61499 reference model provides an international standard developed specifically for supporting the creation of distributed event-based automation systems. Functionality is abstracted into function blocks which can be coded graphically as well as via a text-based method. As one of the design goals was the ability to support distributed control applications, communication plays a central role in the IEC 61499 specification. In order to enable the deployment of functionality to distributed platforms, these platforms need to exchange data in a variety of protocols. IEC 61499 realizes the support of these protocols via "Service Interface Function Blocks" (SIFBs). In the context of smart grids and energy applications, IEC 61499 could play an important role, as these applications require coordinating several distributed control logics. Yet, the support of grid-related protocols is a pre-condition for a wide-spread utilization of IEC 61499. The eXtensible Messaging and Presence Protocol (XMPP) on the other hand is a well-established protocol for messaging, which has recently been adopted for smart grid communication. Thus, SIFBs for XMPP facilitate distributed control applications, which use XMPP for exchanging all control relevant data, being realized with the help of IEC 61499. This paper introduces the idea of integrating XMPP into SIFBs, demonstrates the prototypical implementation in an open source IEC 61499 platform and provides an evaluation of the feasibility of the result.Comment: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA

Federation of AAL & AHA systems through semantically interoperable framework

[EN] Ambient Assisted Living (AAL) and Active and Healthy Ageing (AHA) immensely benefit from IoT application. The federation of IoT platforms can multiply the benefits obtained by the operation of those systems in an isolated way, as it enables important synergies (e.g., intelligent information sharing, system cooperation, service enhancement). This federation requires the enablement of interoperability between the IoT systems, which represents a major challenge, as systems typically follow very different standards, data formats, semantic models and manners of representing the information. We have provided a technical solution in the frame of ACTIVAGE, a project that aims to federate multiple heterogeneous IoT platforms and systems associated to clusters of AHA Smart Homes in 12 regions across Europe, with the goal to improve the AHA service provided and create the first European AHA ecosystem. Our technical solution allows the enablement of full semantic interoperability across heterogeneous platforms and it has been validated in a test scenario. It enables significant AHA service enhancement within the ACTIVAGE ecosystem, as native applications from one platform could be used indistinctly by all federated platforms. Our solution allows good scalability federating new platforms, with linear and relatively low effort.This research work has been partially funded by LSP H2020 ACTIVAGE project under Grant Agreement Nº 732679.González-Usach, R.; Julián, M.; Esteve Domingo, M.; Palau Salvador, CE. (2021). Federation of AAL & AHA systems through semantically interoperable framework. 1-6. https://doi.org/10.1109/ICCWorkshops50388.2021.94735031

NILM techniques for intelligent home energy management and ambient assisted living: a review

The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes, of the voltage. Energy disaggregation is intended to separate the total power consumption into specific appliance loads, which can be achieved by applying Non-Intrusive Load Monitoring (NILM) techniques with a minimum invasion of privacy. NILM techniques are becoming more and more widespread in recent years, as a consequence of the interest companies and consumers have in efficient energy consumption and management. This work presents a detailed review of NILM methods, focusing particularly on recent proposals and their applications, particularly in the areas of Home Energy Management Systems (HEMS) and Ambient Assisted Living (AAL), where the ability to determine the on/off status of certain devices can provide key information for making further decisions. As well as complementing previous reviews on the NILM field and providing a discussion of the applications of NILM in HEMS and AAL, this paper provides guidelines for future research in these topics.Agência financiadora: Programa Operacional Portugal 2020 and Programa Operacional Regional do Algarve 01/SAICT/2018/39578 Fundação para a Ciência e Tecnologia through IDMEC, under LAETA: SFRH/BSAB/142998/2018 SFRH/BSAB/142997/2018 UID/EMS/50022/2019 Junta de Comunidades de Castilla-La-Mancha, Spain: SBPLY/17/180501/000392 Spanish Ministry of Economy, Industry and Competitiveness (SOC-PLC project): TEC2015-64835-C3-2-R MINECO/FEDERinfo:eu-repo/semantics/publishedVersio